The future of travel chatbot technology

Gone are those days when travel companies could shoot emails full of deals and offers and visitors would still convert into customers. Customers are now looking for neat and personalized emails with deals targeted specifically to them based on their travel patterns. Travel chatbot or the chatbot technology is one such advancement powered by Artificial Intelligence and complex algorithms that collect travellers’ data, analyse it, observe travel behaviour and patterns, and produce personalized deals for customers. This Mobile Travel Chat (MTC) or Mobile Travel Concierge technology appeared last year that harnesses the power of machine learning and natural language recognition to offer personal and hassle-free experience compared to OTAs, because of the way it interacts with the users. The future of the travel chatbot technology looks bright as AI is able to learn users’ preferences and formulate data a lot faster than humans can. Let’s take a more in-depth look in the travel chatbot technology and see what we can expect from it in 2017 –

Expected travel chatbot trends in 2017:

Huge improvement in the booking process –

Despite the advancements, booking travel is still a complicated process for travellers. From researching for the perfect destination to finding the perfect deal, a traveller still has to go through a long process. The travel chatbot technology will make this process quicker by learning user behaviour and patterns in the background. From simple data like booking destinations and dates to complex and detailed data like inclination toward particular airline or hotel or time of travel, travel chatbots will personalize travel for users a lot better than travel agents can, that too at a fraction of the time. It may not be immediately apparent how the chatbot technology can make things simpler given the multiple layers of information but there are plenty of areas in the travel booking process where this technology can be implemented to enhance the user experience immensely.

More complex algorithms –

The travel booking process has an unusually long funnel compared to other economic sectors mainly because in the primary stages of the process, the customer is not sure of the details of the trip – like where he wants to spend his vacation, which are the top vacations suited for his travel patterns, and where he would get the best bang for buck. Travellers further down the funnel might be business travellers or frequent fliers, who are experienced and capable of booking their own travel with less or no guidance while some travellers would need more guidance regarding the destinations. Also, travellers at different stages have different information requirements and the current travel chatbot technology is not advanced enough to reflect multiple variables. We will soon see complex chatbots that would differentiate travellers either by learning them or offering them an option to specify their requirements.

Specific purpose travel chatbot –

The usual approach in the travel chatbot design phase is to design the chatbot first and then think about customers’ needs. This approach has led to chatbots that are not able to meet the requirements or deliver their purpose. The perfect method while developing a chatbot is to visualize the requirement and then develop a solution that solves the particular consumer problem. A scenario where the travel chatbot seems the perfect solution is where the task the bot is resolving has clearly defined parameters as it is difficult to design a bot that will suit all consumer needs. The travel chatbot technology is expected to get more sophisticated by the day and show a lot of progress over the next 12 months.

Natural and conversational experience –

Brands that are building a chatbot need to provide customers with information first about how to structure their queries and a product resolution to the problem is likely. In this manner, the customers will know how to use the chatbot technology for their benefit. It is also essential that the travel chatbot experience be as natural and intuitive to the user as possible. Using natural language processing and complex algorithms, the interaction can be made conversational and such small tweaks to the travel chatbots are expected to bring big changes in the experience of the customer.

More customer information –

The current bottleneck in the travel chatbot technology is lack of sufficient customer information. Customers need to provide as much data about their travel patterns as required which will facilitate chatbots to automate key steps in the booking process in a much better way. For instance, if customers allow collection of their data when they are browsing for destinations, chatbots will be able to collect it and offer more tailored results based on the customers’ inclination towards certain destinations or activity or hotel. Similarly, customers can set communication to be offered either via notifications or via emails or sms about deals and offers for particular locations or dates. The more data chatbots get, the better results are expected to be produced.

Avoiding too much in one app –

The key to capitalizing on chatbots is to think small first. Travel companies are expected to isolate pain points in the booking funnel and find out if they can be resolved using conversational function. It is important for travel companies to be careful as there is a high price to pay for implementing a chatbot incorrectly. The ideal solution to this problem is to focus on one or two functions at first and then learn based on the data that is gathered.

What are your thoughts on the travel chatbot technology? Do you think this technology will bring a revolution in the travel industry? Please drop your views in the comments section below and connect with us on Facebook, Twitter, Google+ and Linkedin.

Share

— Yogesh Tandel

Multi-talented Project Manager and programmer, having worked on HTML, Actionscript, Android and Blackberry technologies, as well as design. Is passionate about mobile development and heads the mobile team at Qtech. A positive thinker with indomitable optimism and a will-do spirit. Is currently learning Swift. When he isn't researching on the latest in mobile technology, he hits the road on his Harley Davidson.